« DIMACS 2024 Workshop on Forecasting
October 14, 2024
Location:
The Rutgers Club
Livingston Campus
85 Avenue E, Piscataway, NJ 08854
Organizer(s):
Raf Frongillo, University of Colorado
David Pennock, DIMACS
Jens Witkowski, Frankfurt School of Finance & Management
Following the successful iterations at EC 2017 and DIMACS 2021, we seek submissions to the DIMACS 2024 Workshop on Forecasting. The workshop will be held on October 14, 2024, at Rutgers University New Brunswick, NJ, co-located with the 8th International Conference on Algorithmic Decision Theory (ADT 2024). We welcome submissions describing recent research on crowd-sourced, data-driven, or hybrid approaches to forecasting.
In this workshop, we will bring together computer scientists, economists, statisticians, and decision scientists, some who develop theories of forecasting and others who study it empirically. We invite academics together with practitioners who build forecasting platforms, operate forecasting competitions, and publish predictions. Our primary focus is on what happens after predictive models have been trained or formed; that said, still in scope are data-driven and machine-learning-based techniques that aggregate forecasts and other information to harness the so-called wisdom of the crowd.
Topics of interest for the workshop include but are not limited to:
Monday, October 14, 2024
Breakfast and Registration
Opening Remarks
Dan Goldstein, Microsoft Research
Understanding People’s Preferences for Predictions: People Prioritize Being Right over Minimizing How Wrong They Are in Expectation
Berkeley J. Dietvorst, University of Chicago Booth School of Business
The Pick-the-Winner-Picker Heuristic: Preference for Categorically Correct Forecasts
Jay Naborn, Washington University, St. Louis
Break
Can Language Models Use Forecasting Strategies?
Seth Blumberg, Google
Choices of Property Indirect-elicitation for Parametric Model Estimations
Ian Kash, University of Illinois, Chicago
Keynote Speaker: Self-Resolving Prediction Markets for Unverifiable Outcomes
Yiling Chen, Harvard University
Lunch
Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
Anish Thilagar, University of Colorado
High-Effort Crowds: Limited Liability via Tournaments
Yichi Zhang, University of Michigan
Information Aggregation with Costly Information Acquisition
Spyros Galanis, Durham University
Regularized Aggregation of Point Predictions from Experts with Different Amounts of Past Performance Data
Junnan Wang, INSEAD
Break
Keynote Speaker: Full Inference Cycle Forecasting with an Application to Nuclear Risk
Ezra Karger, Federal Reserve Bank of Chicago
Panel Discussion on Prediction Markets Moderator: Harry Crane, Rutgers University
Molly Hickman, Metaculus
Kelly Littlepage, OneChronos
Flip Pidot, American Civics Exchange
Ethan Rosen, PredictIt
Xavier Sottile, Kalshi
Lightning Talks
Wrap Up and Discussion
Poster Session and Reception, joint with ADT 2024
We invite both full contributions and poster contributions. A full contribution is an unpublished or recently published research manuscript. A poster contribution can be a preprint, a recently published paper, an abstract, or a presentation file. Preference may be given to more recent and unpublished work. We especially encourage poster contributions from students and postdocs.
Please submit your contributions using the link https://forms.gle/xNbQSrEjxTawRPRB8 by August 2, 2024. The workshop is non-archival, meaning contributors are free to publish their results later in archival journals or conferences. Email questions or suggestions to the organizers.
The workshop will include invited and contributed talks, open and/or panel discussion, and a poster session. Workshop registration is open to all but you must register to attend.
Important Dates
Submissions due: Friday, August 2, 2024. (AoE)
Notifications: Friday, August 9, 2024
Workshop Date: Monday, October 14, 2024
Travel: The DIMACS travel page has information about traveling to the workshop, including transportation and hotel options. Most workshop participants will be staying at the Heldrich Hotel in downtown New Brunswick NJ.
Parking: All registered participants for the workshop will receive an email with a link to register their car closer to the workshop. If you do not have a Rutgers parking permit and plan to drive to the workshop you must register your car to park.
Presented in association with the SF on Mechanisms & Algorithms to Augment Human Decision Making.